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Update app.py (#2)
Browse files- Update app.py (baaac941d352601fe7ca90116934fa8863462635)
Co-authored-by: Abubakar Abid <[email protected]>
app.py
CHANGED
@@ -8,6 +8,8 @@ import gradio as gr
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import requests
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from transformers import pipeline
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demo = gr.Blocks()
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with demo:
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@@ -26,11 +28,12 @@ with demo:
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# Generate model prediction
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# Default model: distilbert-base-uncased-finetuned-sst-2-english
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def _predict(txt, tgt, state):
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pipe = pipeline("sentiment-analysis")
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pred = pipe(txt)[0]
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pred["label"] = pred["label"].title()
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ret = f"Target: {tgt}
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if pred["label"] != tgt:
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state["fooled"] += 1
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ret += " You fooled the model! Well done!"
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@@ -43,13 +46,14 @@ with demo:
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toggle_final_submit = gr.update(visible=done)
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toggle_example_submit = gr.update(visible=not done)
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new_state_md = f"State: {state['cnt']}/{total_cnt} ({state['fooled']} fooled)"
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return ret, state, toggle_example_submit, toggle_final_submit, new_state_md
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# Input fields
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text_input = gr.Textbox(placeholder="Enter model-fooling statement", show_label=False)
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labels = ["Positive", "Negative"]
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random.shuffle(labels)
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label_input = gr.Radio(choices=labels, label="Target (correct) label")
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text_output = gr.Markdown()
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with gr.Column() as example_submit:
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submit_ex_button = gr.Button("Submit")
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@@ -69,7 +73,7 @@ with demo:
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submit_ex_button.click(
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_predict,
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inputs=[text_input, label_input, state],
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outputs=[text_output, state, example_submit, final_submit, state_display],
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)
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submit_hit_button.click(
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@@ -79,4 +83,4 @@ with demo:
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_js="function(state, dummy) { return [state, window.location.search]; }",
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)
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demo.launch(favicon_path="https://huggingface.co/favicon.ico")
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import requests
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from transformers import pipeline
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pipe = pipeline("sentiment-analysis")
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demo = gr.Blocks()
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with demo:
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# Generate model prediction
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# Default model: distilbert-base-uncased-finetuned-sst-2-english
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def _predict(txt, tgt, state):
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pred = pipe(txt)[0]
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other_label = 'negative' if pred['label'].lower() == "positive" else "positive"
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pred_confidences = {pred['label'].lower(): pred['score'], other_label: 1 - pred['score']}
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pred["label"] = pred["label"].title()
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ret = f"Target: **{tgt}**. Model prediction: **{pred['label']}**\n\n"
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if pred["label"] != tgt:
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state["fooled"] += 1
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ret += " You fooled the model! Well done!"
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toggle_final_submit = gr.update(visible=done)
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toggle_example_submit = gr.update(visible=not done)
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new_state_md = f"State: {state['cnt']}/{total_cnt} ({state['fooled']} fooled)"
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return pred_confidences, ret, state, toggle_example_submit, toggle_final_submit, new_state_md
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# Input fields
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text_input = gr.Textbox(placeholder="Enter model-fooling statement", show_label=False)
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labels = ["Positive", "Negative"]
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random.shuffle(labels)
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label_input = gr.Radio(choices=labels, label="Target (correct) label")
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label_output = gr.Label()
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text_output = gr.Markdown()
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with gr.Column() as example_submit:
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submit_ex_button = gr.Button("Submit")
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submit_ex_button.click(
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_predict,
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inputs=[text_input, label_input, state],
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outputs=[label_output, text_output, state, example_submit, final_submit, state_display],
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)
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submit_hit_button.click(
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_js="function(state, dummy) { return [state, window.location.search]; }",
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)
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demo.launch(favicon_path="https://huggingface.co/favicon.ico")
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